existing cluster: existing_arrikto: update docs on options for installing on...

existing cluster: existing_arrikto: update docs on options for installing on existing K8s clusters (#861)

* platform-existing: add docs for deploying on existing k8s cluster
Signed-off-by: NYannis Zarkadas <yanniszark@arrikto.com>

* fix according to review
Signed-off-by: NYannis Zarkadas <yanniszark@arrikto.com>

content/docs/started/getting-started-k8s.md

@@ -4,84 +4,157 @@ description = "Instructions for installing Kubeflow on your existing Kubernetes
 weight = 4
 +++
 
-Follow these instructions if you want to install Kubeflow on an existing Kubernetes
-cluster.
+Follow these instructions if you want to install Kubeflow on an existing Kubernetes cluster.
 
-If you are using a Kubernetes distribution or Cloud Provider which has specific
-instructions for installing Kubeflow we recommend following those instructions.
-Those instructions do additional Cloud specific setup to create a really great 
-Kubeflow experience.
+If you are using a Kubernetes distribution or Cloud Provider which has specific instructions for installing Kubeflow we recommend following those instructions. Those instructions do additional Cloud specific setup to create a really great Kubeflow experience.
 
-You can use either [kind](https://github.com/kubernetes-sigs/kind#installation-and-usage) or
-[Minikube](https://kubernetes.io/docs/tasks/tools/install-minikube/) to install a Kubernetes cluster and it
-is recommended to use [kind](https://github.com/kubernetes-sigs/kind#installation-and-usage)
-as it is more simple to install.
+For installing Kubeflow on an existing Kubernetes Cluster, you can use one of the following options:
 
-Before installing Kubeflow on the command line:
+* [Kubeflow for Existing Clusters by Arrikto](#Kubeflow-for-Existing-Clusters---by-Arrikto)
 
-  * Ensure you have installed the following tools:
-    
-     * [kubectl](https://kubernetes.io/docs/tasks/tools/install-kubectl/)
-     * [ks] (https://github.com/ksonnet/ksonnet/releases/)
+## Kubeflow for Existing Clusters - by Arrikto
 
+This installation of Kubeflow is maintained by [Arrikto](https://www.arrikto.com/), is geared towards existing Kubernetes clusters and does not depend on any cloud-specific feature.
 
-## Deploy Kubeflow
+In this reference architecture, we use [Dex](https://github.com/dexidp/dex) and [Istio](https://istio.io/) for vendor-neutral authentication.
 
-Follow these steps to deploy Kubeflow:
+![platform existing architecture](https://i.imgur.com/OlaN73j.png)
+
+### Prerequisites
+- Kubernetes Cluster with LoadBalancer support.
+
+If you don't have a Kubernetes Cluster, you can create a compliant Kubernetes Engine (GKE) on Google Cloud Platform cluster with the following script:
+
+<details>
+
+<summary>GKE Cluster Creation Script</summary>
+
+```bash
+#!/bin/bash
+
+set -e
+
+# This script uses the gcloud command.
+# For more info, visit: https://cloud.google.com/sdk/gcloud/reference/container/
+
+# Edit according to your preference
+GCP_USER="$(gcloud config list account --format "value(core.account)")"
+GCP_PROJECT="$(gcloud config list project --format "value(core.project)")"
+GCP_ZONE="us-west1-b"
+
+CLUSTER_VERSION="$(gcloud container get-server-config --format="value(validMasterVersions[0])")" 
+CLUSTER_NAME="kubeflow"
+
+############################
+# Create and setup cluster #
+############################
 
-1. Download a `kfctl` release from the 
-  [Kubeflow releases page](https://github.com/kubeflow/kubeflow/releases/).
+gcloud container clusters create ${CLUSTER_NAME} \
+--project ${GCP_PROJECT} \
+--zone ${GCP_ZONE} \
+--cluster-version ${CLUSTER_VERSION} \
+--machine-type "n1-standard-8" --num-nodes "1" \
+--image-type "UBUNTU" \
+--disk-type "pd-ssd" --disk-size "50" \
+--no-enable-cloud-logging --no-enable-cloud-monitoring \
+--no-enable-ip-alias \
+--enable-autoupgrade --enable-autorepair
 
-1. Unpack the tar ball:
+echo "Getting credentials for newly created cluster..."
+gcloud container clusters get-credentials ${CLUSTER_NAME} --zone=${GCP_ZONE}
+
+echo "Setting up GKE RBAC..."
+kubectl create clusterrolebinding cluster-admin-binding --clusterrole=cluster-admin --user=${GCP_USER}
+```
+
+</details>
+
+### Deploy Kubeflow
+
+Follow these steps to deploy Kubeflow:
+
+1. Download a `kfctl` release from the [Kubeflow releases page](https://github.com/kubeflow/kubeflow/releases/) and unpack it:
 
     ```
     tar -xvf kfctl_<release tag>_<platform>.tar.gz
     ```
 
-1. Run the following commands to set up and deploy Kubeflow. The code below
-  includes an optional command to add the binary `kfctl` to your path. If you 
-  don't add the binary to your path, you must use the full path to the `kfctl` 
-  binary each time you run it.
-
-    ```bash
-    # The following command is optional, to make kfctl binary easier to use.
-    export PATH=$PATH:<path to kfctl in your kubeflow installation>
-
-    export KFAPP=<your choice of application directory name>
-    # Default uses IAP.
-    kfctl init ${KFAPP}
-    cd ${KFAPP}
-    kfctl generate all -V
-    kfctl apply all -V
+    Alternatively, you can build the `kfctl` binary yourself:
+
     ```
-   * **${KFAPP}** - the _name_ of a directory where you want Kubeflow 
-     configurations to be stored. This directory is created when you run
-     `kfctl init`. If you want a custom deployment name, specify that name here.
-     The value of this variable becomes the name of your deployment.
-     The value of this variable cannot be greater than 25 characters. It must
-     contain just the directory name, not the full path to the directory.
-     The content of this directory is described in the next section.
+    git clone https://github.com/kubeflow/kubeflow.git
+    cd kubeflow/bootstrap
+    make build-kfctl-container
+    ```    
 
-1. Check the resources deployed in namespace `kubeflow`:
+1. Run the following commands to set up and deploy Kubeflow. The code below includes an optional command to add the binary `kfctl` to your path. If you don't add the binary to your path, you must use the full path to the `kfctl` binary each time you run it.
 
-    ```
-    kubectl -n kubeflow get  all
-    ```
+```bash
+# Add kfctl to PATH, to make the kfctl binary easier to use.
+export PATH=$PATH:"<path to kfctl>"
+export KFAPP="<your choice of application directory name>"
+export CONFIG="https://raw.githubusercontent.com/kubeflow/kubeflow/master/bootstrap/config/kfctl_existing_arrikto.0.6.yaml"
+
+# Specify credentials for the default user.
+export KUBEFLOW_USER_EMAIL="admin@kubeflow.org"
+export KUBEFLOW_PASSWORD="12341234"
 
-## Delete Kubeflow
+kfctl init ${KFAPP} --config=${CONFIG} -V
+cd ${KFAPP}
+kfctl generate all -V
+kfctl apply all -V
+```
+
+ * **${KFAPP}** - the _name_ of a directory where you want Kubeflow 
+  configurations to be stored. This directory is created when you run
+  `kfctl init`. If you want a custom deployment name, specify that name here.
+  The value of this variable becomes the name of your deployment.
+  The value of this variable cannot be greater than 25 characters. It must
+  contain just the directory name, not the full path to the directory.
+  The content of this directory is described in the next section.
+
+
+### Accessing Kubeflow
+
+##### Log in as a static user
+
+After deploying Kubeflow, the Kubeflow Dashboard is available at the Istio Gateway IP.
+To get the Istio Gateway IP, run:
+
+```bash
+kubectl get svc -n istio-system istio-ingressgateway -o jsonpath='{.status.loadBalancer.ingress[0].ip}'
+```
+
+Get the IP and open it in a browser: `https://<ip>/`.
+
+Enter the credentials you specified in `KUBEFLOW_USER_EMAIL`, `KUBEFLOW_PASSWORD` and access the Kubeflow Dashboard!
+
+#### Add static users for basic auth
+
+To add users to basic auth, you just have to edit the Dex ConfigMap under the key `staticPasswords`.
+```bash
+# Download the dex config
+kubectl get cm dex -n kubeflow -o jsonpath='{.data.config\.yaml}' > dex-config.yaml
+
+# Edit the dex config with extra users.
+# The password must be hashed with bcrypt with an at least 10 difficulty level.
+# You can use an online tool like: https://passwordhashing.com/BCrypt
+
+# After editing the config, update the ConfigMap
+kubectl create cm dex --from-file=config.yaml=dex-config.yaml --dry-run -oyaml | kubectl apply -f -
+```
+
+### Delete Kubeflow
 
 Run the following commands to delete your deployment and reclaim all resources:
 
 ```
 cd ${KFAPP}
-# If you want to delete all the resources, including storage.
-kfctl delete all --delete_storage
-# If you want to preserve storage, which contains metadata and information
-# from mlpipeline.
+# If you want to delete all the resources, run:
 kfctl delete all
 ```
 
-## Understanding the deployment process
+### Understanding the deployment process
 
 The deployment process is controlled by 4 different commands:
 
@@ -95,34 +168,19 @@ set of resources to apply the command to; this argument can be one of the
 following:
 
 * **k8s** - all resources that run on Kubernetes.
-* **all** - GCP and Kubernetes resources.
+* **all** - platform and Kubernetes resources.
 
-### App layout
+#### App layout
 
 Your Kubeflow app directory contains the following files and directories:
 
-* **app.yaml** defines configurations related to your Kubeflow deployment.
-
-  * The values are set when you run `kfctl init`.
-  * The values are snapshotted inside **app.yaml** to make your app 
-    self contained.
-
-  * The directory is created when you run `kfctl generate platform`.
-  * You can modify these configurations to customize your GCP infrastructure.
-
-* **${KFAPP}/k8s_specs** is a directory that contains YAML specifications
-  for some daemons deployed on your Kubernetes Engine cluster.
-
-* **${KFAPP}/ks_app** is a directory that contains the 
-  [ksonnet](https://ksonnet.io) application for Kubeflow.
-
-  * The directory is created when you run `kfctl generate`.
-  * You can use ksonnet to customize Kubeflow.
+* **${KFAPP}/app.yaml** defines configurations related to your Kubeflow deployment.
+* **${KFAPP}/kustomize**: contains the YAML manifests that will be deployed.
 
-## Next steps
+### Next steps
 
 * Follow the instructions to [connect to the Kubeflow web 
   UIs](/docs/other-guides/accessing-uis/), where you can manage various 
   aspects of your Kubeflow deployment.
 * Run a [sample machine learning workflow](/docs/examples/resources/).
-* Get started with [Kubeflow Pipelines](/docs/pipelines/pipelines-quickstart/).
+* Get started with [Kubeflow Pipelines](/docs/pipelines/pipelines-quickstart/)
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